Deep Reinforcement Learning and GANs Advanced Topics in Deep Learning
6+ Hours of Video Instruction An intuitive introduction to the latest developments in Deep Learning. Overview Deep Reinforcement Learning and GANs LiveLessons is an introduction to two of the most exciting topics in Deep Learning today. Generative Adversarial Networks cast two Deep Learning netwo...
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| Idioma: | Inglés |
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Addison-Wesley Professional
2018.
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| Edición: | 1st edition |
| Colección: | LiveLessons
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| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009631089806719 |
| Sumario: | 6+ Hours of Video Instruction An intuitive introduction to the latest developments in Deep Learning. Overview Deep Reinforcement Learning and GANs LiveLessons is an introduction to two of the most exciting topics in Deep Learning today. Generative Adversarial Networks cast two Deep Learning networks against each other in a “forger-detective” relationship, enabling the fabrication of stunning, photorealistic images with flexible, user-specifiable elements. Deep Reinforcement Learning has produced equally surprising advances, including the bulk of the most widely-publicized “artificial intelligence” breakthroughs. Deep RL involves training an “agent” to become adept in given “environments,” enabling algorithms to meet or surpass human-level performance on a diverse range of complex challenges, including Atari video games, the board game Go, and subtle hand-manipulation tasks. Throughout these lessons, essential theory is brought to life with intuitive explanations and interactive, hands-on Jupyter notebook demos. Examples feature Python and Keras, the high-level API for TensorFlow, the most popular Deep Learning library. The companion materials for this LiveLesson can be found at https://github.com/the-deep-learners/TensorFlow-LiveLessons/ . About the Instructor Jon Krohn is Chief Data Scientist at untapt, a machine-learning startup in New York. He presents an acclaimed series of tutorials on artificial neural networks, including Deep Learning with TensorFlow LiveLessons and Deep Learning for Natural Language Processing LiveLessons . He also teaches his curriculum in-classroom at the NYC Data Science Academy. Jon holds a doctorate in neuroscience from Oxford University and has been publishing on machine learning in leading academic journals since 2010. Skill Level Intermediate Learn How To Understand the high-level theory and key language around deep reinforcement learning and generative adversarial networks Architect GANs that create convincing images in the style of human-drawn illustrations Build deep RL agents that become adept at performing in a wide variety of environments, such as those provided by OpenAI Gym Run automated experiments for optimizing deep reinforcement learning agent parameters, such as its artificial-neural-network configuration Appreciate what the current limitations of “artificial intelligence” are and how they may be overcome in the near future Who Should Take This Course Perfectly suited to software engineers, data... |
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| Notas: | Title from title screen (Safari, viewed March 12, 2018). Release date from resource description page (Safari, viewed March 12, 2018). |
| Descripción Física: | 1 online resource (1 video file, approximately 5 hr., 4 min.) |
